Part 2 MS-Copilot: From Using Copilot to Engineering AI-Enabled Auditing

Topics:

Precondition: Participation in Part 1 “Leverage MS Copilot to Innovate Your Audit Workflow”

Learning Objectives
Participants will be able to:

• Design advanced Copilot audit use cases across planning, fieldwork,
  reporting, and follow-up
• Translate audit methodology into AI-supported workflows
• Develop a structured prompt library aligned with the internal audit value chain
• Conceptually design and test Copilot Agents for Internal Audit
• Apply governance, quality, and assurance principles to Copilot-based auditing
• Build a roadmap for scaling Copilot beyond individual use cases

1. From Copilot Usage to Copilot Architecture in Internal Audit

• Key learnings from Part 1 and typical limitations of “ad-hoc prompting”
• Why Internal Audit needs structured AI design, not just AI usage
• Positioning Copilot within the Internal Audit Methodology and QAIP
• Link to the 2025 Global Internal Audit Standards (quality, consistency, professional judgment)

2. Advanced Audit Use Cases with MS Copilot Across the Audit Value Chain

Audit Planning & Risk Assessment

• AI-supported Continuous Audit Risk Assessment (CARA)
• Copilot-supported analysis of risk signals, KRIs, incidents, and management reports
• Generating dynamic audit scopes and risk-based audit programs

Audit Fieldwork

• Copilot-assisted control design and operating effectiveness analysis
• Intelligent interview preparation and interview summary synthesis
• Risk orientated walkthrough documentation and issue hypothesis generation

Audit Reporting

• AI-supported root cause analysis structuring
• Drafting issue narratives aligned with stakeholder level (management vs. board)
• Consistency checks across findings, ratings, and recommendations

Follow-up & Continuous Assurance

• Copilot-based issue tracking and trend analysis

Workshop:

• Participants map their own audit value chain and identify high-impact Copilot use cases.

3. Working with Microsoft Copilot Studio and Copilot Agents

• What Copilot Studio is – and what it is not
• When to use standard Copilot vs. Studio vs. Agents
• Designing Copilot Agents for Internal Audit

Conceptual Lab:

Designing a prototype Copilot Agent for a selected audit scenario (no IT skills required – focus on logic, inputs, outputs, controls)

4. Designing an MS Copilot Prompt Library for Internal Auditors

• Why professional audit prompting is different from generic prompting
• ARC Certified Copilot Prompt Pack for Internal Audit
• Copilot Audit Use Case Catalogue (Planning → Reporting)
• Prompt design principles along different audit sub-processes
• Prompt quality criteria (reliability, reproducibility, bias awareness)

5. Governance, Quality, and Ethical Guardrails for Copilot in Internal Audit

• Preventing over-reliance on AI-generated outputs
• Ensuring audit evidence quality and professional judgment
• Embedding Copilot into audit methodology and QAIP

6. Scaling Copilot in the Internal Audit Function

• Maturity model: From personal productivity to institutional capability
• Defining “AI-enabled audit standards” internally
• Building a Copilot Center of Excellence within Internal Audit

Action Planning Session:

• Participants develop a Copilot scaling roadmap for their audit function.

7. Conclusion and Takeaways

• Key insights from advanced Copilot usage
• What Internal Audit should standardize, what should remain flexible
• Personal and departmental next steps
• Open discussion: risks, limits, and future opportunities